1. Field of the Invention
The present invention relates to a time-series data analyzing apparatus, time-series data analyzing method and time-series data analyzing program for analyzing multivariate time series data.
2. Description of the Related Art
Typical methods for analyzing data taking into account composite factor include covariance analysis (ANCOVA), covariance structure analysis, hidden Markov model (HMM) and the like. However, methods such as the covariance analysis method require strict prerequisites such as normality of distribution and parallelism of regression line of each factor; and the hidden Markov model method and the like require an analyzer to consider dependency relationship carefully before analysis. Therefore, if there is no way for finding out what composite factor has occurred, it is difficult to analyze what structure the composite factor has. For these reasons, it is considered difficult to take out a composite transitional pattern from a large amount of data or complicated data without a hypothetical basis.
“Disease Condition Control Method and System” of Jpn. Pat. Appln. KOKAI No. 10-198750 has disclosed a method for obtaining associated rule for discriminating a patient in a critical condition using his disease history and disease intervention history. However, this method is constructed to determine a patient to be intervened and it is considered difficult to pick out only the related composite factor.
Although “Health Control Assistant System” of Jpn. Pat. Appln. KOKAI No. 2004-348432 has disclosed a system intended for improvement of lifestyle habits based on doctor inquiry items for prevention or improvement of lifestyle disease, this system does not aim at the time-series analysis using inspection values and doctor inquiry data.
“Health Instruction Assistant System, Server, Client Terminal and Health Instruction Assistant Program” of Jpn. Pat. Appln. KOKAI No. 2004-21854 has disclosed a system for assisting instruction about lifestyle habits such as diet control and physical exercise to chronic disease patients in medical institutions. This system presents user an advice about improvement of blood pressure and other items depending on his or her symptom from replies of diagnostic table including inspection values and doctor inquiry. Although this Jpn. Pat. Appln. KOKAI No. 2004-21854 has described about a trend graph in which time-series values are plotted, it has described nothing about finding out a composite factor from the time-series data.